Structured query language or SQL is used as a way communication with the relational database management systems. This standardized language helps data analysts to analyze, recover and update data or records that are contained inside the database. This tool is also used to store structured data.

There are a variety of popular databases, including Oracle, Microsoft Access or Server, and each of these has minor differences as they belong to different brands, while the structure of the language is more or less the same. SQL shows the users to the data in the records via the following instructions executed in the syntax:

  • Order by: This enables you to sort data results in according to your choice (for example, alphabetical order)
  • From: This provides knowledge on the table or location from where the data is being retrieved or updated.
  • Where: This means the rows that are included in the query

SQL queries are formulated to perform a wide range of tasks, including maintaining and analyzing structured data. Though the use of SQL could vary from one person to other, as well as business requirements, some of the common applications include:

  • Defines database user rights
  • Add, edit or delete data records
  • Connecting or joining data records that come from multiple tables
  • Editing or creating the data dictionary of definitions
  • Locking or managing data tables.

This standard tool helps users to maintain a variety of functionalities, such as record management, quality control, and data analysis. With SQL, you can easily complete all communications with or within the databases.

You can use Excel or Spreadsheet apps to store small parts of data that are less in number. This could reach up to a thousand records. But, what can you do when the record list exceeds thousands, say above hundreds of millions or thousands of transactions or data records? This is where SQL has a great role to play in dealing and managing the whole database and these include:

  • Storage capacity
  • Speed
  • Multi-user access
  • Excellent querying
  • Quality control over data

SQL is the best choice for data analytics as it presents a lot more sustainability when it comes to dealing with greater and large pieces of data. If you want your data assets to display a greater deal of extension, then the SQL database is the best environment to help you enjoy a great transition.

We can simply say that SQL is that structured language, which can be used to create, maintain and manage the data that lies within a database. The description for a database is that it is a structured architecture that has been programmed to organize data, defined by metadata, which ultimately represents the structure.

The Role of SQL in DBMS

  1. Defining Data

It is commonly referred to as data definition, allowing the database administrator to simply define the structure of stored data and organize these in a structured manner, while also defining the connections between each of the stored data.

  1. Data Retrieval

The data retrieval is how SQL controls a user program or application to extract data stored in a computer’s database and utilize it efficiently.

  1. Data Manipulation

Data manipulation is how SQL powers a user program to ensure that the computer’s database is updated. It achieves this by removing old data and adding new ones.

  1. Access control

SQL applies this to deploy user access based on permissions for recovering or changing data that is stored, thus protecting your information from any third parties that are denied access.

  1. Data sharing

This allows data coordination and sharing while assuring that the users don’t overlap the permissions provided to one another.

  1. Data Integrity

The data integrity process is used to define the integrity constraints blocking the corruption of data, that occurs due to irregular system updates or failures.

Though the relational database (RDBMS) has been playing a leading role as a dormant model of a database, the non-relational cloud or NoSQL database is substituting these traditional norms.

NoSQL is an approach apart from the traditional technologies performed by relational database management systems (RDBMS). RDBMS performs SQL, which we have discussed in the aforementioned points. As you are aware, RDBMS largely relies on rows, columns, schemas, and tables, for recovering and organizing data stored in the databases, all this works differently when it comes to NoSQL.

NoSQL databases can perform their functionalities and carry out their operations without the help of any of these structures. They are capable of implementing more flexible data models. NoSQL is also known as not only SQL or not SQL performs techniques that help in avoiding repetitions and differences that pop up usually when the traditional technologies of RDBMS are performed. RDBMS comes with certain areas of concerns, such as non-scalability, non-flexibility, and performance problems, in which the modern-day applications are looking for NoSQL solves all these intensive scenarios and helps data-intensive apps to grow.

Whenever there is a lot of unstructured data that needs storage, NoSQL can be used as it can provide structured data largely which fail to fit inside the traditional relational schemas or RDBMS. Some of the common unstructured data include: chat, messaging, log data, user and session data, large data such as videos and images as well as internet of things and device data.

Types of NoSQL or Non-SQL

  • Wide-column NoSQL
  • Graph stores
  • Key-value data stores
  • Document stores

Based on your project specifications, user needs, and data-intensiveness, you can choose the one that fits all the needs within an affordable budget.

SQL and NoSQL – Advantages and Disadvantages

Advantages of NoSQL

  1. NoSQL is Non-relational

Non-relational, in other words, you can call it as table-less, these NoSQL databases vary from SQL databases. In this sense, they provide ease of management while assuring a high level of flexibility with new data models.

  1. Low Cost of NoSQL

While being low cost, NoSQL is also an open-source database, that provides an awesome solution for smaller businesses to opt this at affordable prices.

The various kinds of NoSQL databases available in the market include Couchbase, Amazon’s Dynamo Db, MongoDB and MarkLogic to provide for the processing of big data apps that are cost-effective.

  1. Easier Scalability

NoSQL has been getting popularity because of the flexibility and scalability that it offers over the other kinds of databases that are available. It has been designed to perform exceptionally well under any conditions including low-cost hardware.

Detailed database model structuring is irrelevant here: You can easily create a database without actually developing any detailed database models when using a NoSQL database. This will help to save a lot of your time and effort.

Disadvantages of NoSQL

  1. Less Community Support

Though the NoSQL has been growing at an incredible pace, the community support is relatively less as its new.

  1. Standardization

It lacks a standardized platform like SQL, which is blocking it from further expanding. This has been creating concerns during migration. Standardization is what helps the database industry to unify.

  1. Interfaces and Interoperability

Interfaces and interoperability is another concern that is faced by NoSQL, which needs fixing quickly.

Advantages of SQL

  1. Speed

As we have already discussed, the speed offered by SQL is unbelievable and unbeatable, helping the retrieval of data from database records with ease.

  1. Well- Defined Standards

Unlike the NoSQL, SQL doesn’t have the issue of standardization. This follows the ISI and ANSI standards, which are approved across the globe.

  1. No Coding

Its code-free nature makes the manner hassle-free.

  1. Data Integration Scripts

One of the main apps of SQL is to write data integration scripts, which further helps data admins and developers.

  1. Analytical Queries

Data analysts use SQL for setting, executing and running analytical queries regularly.

  1. Retrieving Information

It helps to recover the subsets of information within a database. Some of the commonly used elements include insert, select, delete, add truncate, alter and update.

Disadvantages of SQL

  1. Interfaces

Though there are no complex coding involved, the process of interfacing is complex.

  1. Complex Interface

Since SQL has a complex structure, it becomes challenging for certain users to access it.

  1. Implementation

Certain databases implement established extensions to standard SQL to ensure the vendor lock-in.

  1. Partial Control

Since there are certain hidden rules and conditions, the programmers who use SQL do not have power over the database.

  1. Expense

The expenses involved in SQL operation are too much, making it difficult for bringing vendor-in.

Here, we have listed out a summary of both SQL and NoSQL along with their advantages and disadvantages. You can decide the best based upon the business requirements, cost and time you have to implement either of them.

SQL vs NoSQL

  • SQL

SQL uses the ACD compliance mode to protect the integrity of a database. Since it possesses structured data, an integrated support system is not needed for using it with any type of data based on your choice. The predefined structure and schemas of SQL make it the most favored choice for businesses.

  • NoSQL

The increasing popularity of NoSQL is due to its capacity to provide various data types and also the capability to scale by spreading quickly to some servers simultaneously. People prefer NoSQL for developing applications within no time. One of the reasons includes the performance speed.